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this makes it well suited for circuits with strong
nonlinearity
peaked circuits
this makes it well suited for circuits with strong nonlinearity and a high-dimensional set of coupled design parameters
however these methods are not effectively reconfigurable for linearly connected symmetrical structures layouts of contemporary quantum
computers
quantum error correction
however these methods are not effectively reconfigurable for linearly connected symmetrical structures layouts of contemporary quantum computers usually utilizing more ancilla qubits
we investigate the semi-discrete optimal transport ot problem where a continuous source measure mu is transported to a discrete target measure nu with particular attention to the
ot
optimal transport
we investigate the semi-discrete optimal transport ot problem where a continuous source measure mu is transported to a discrete target measure nu with particular attention to the ot map approximation
super-eddington accretion is a crucial phase in the growth of
supermassive
black hole mass
super-eddington accretion is a crucial phase in the growth of supermassive black holes
in the presence of disturbances this improvement idea renders inverse optimal issf controllers
robust
disturbance observer
in the presence of disturbances this improvement idea renders inverse optimal issf controllers robust to gain variations with the same gain margin of 1 2 inf
optical variability is a key observational probe for studying the accretion dynamics and central engine physics of active
galactic
active galactic
optical variability is a key observational probe for studying the accretion dynamics and central engine physics of active galactic nuclei agns
importantly our method operates on probability predictions and event outcomes and
does
learning algorithm
importantly our method operates on probability predictions and event outcomes and does not require under-the-hood access to the machine learning model
the magnitude of strain and the associated increase in the density of states can be tuned by varying the film
thickness
film thickness
the magnitude of strain and the associated increase in the density of states can be tuned by varying the film thickness as systematically confirmed by x-ray diffraction and photoemission spectroscopy measurements
we propose tokenization of events and present a tokenizer spiking patches specifically designed for
event
event cameras
we propose tokenization of events and present a tokenizer spiking patches specifically designed for event cameras
recent advances in data collection and technology enable a deeper understanding of complex urban
commuting
travel information
recent advances in data collection and technology enable a deeper understanding of complex urban commuting yet few studies have rigorously analyzed the temporal stability and origin-destination od heterogeneity of route choice
predicting the adhesion and delamination strength of carbon films on metals by high-throughput
ab
ab initio calculations
predicting the adhesion and delamination strength of carbon films on metals by high-throughput ab initio calculations
we demonstrate that a nonlinear sis can improve communication reliability compared to a linear sis by forming complex signal patterns across the
sis
nonlinear sis
we demonstrate that a nonlinear sis can improve communication reliability compared to a linear sis by forming complex signal patterns across the sis surface which provide higher diversity against noise disturbances while still allowing the receiver to discern these patterns
here we harness the emission of a quantum dot embedded in a micropillar and explore a hybrid approach where the information is encoded on a mixture of single
photons
single photons
here we harness the emission of a quantum dot embedded in a micropillar and explore a hybrid approach where the information is encoded on a mixture of single photons and laser pulses
we also provide a novel static and dynamic decomposition achieving an o k log n -approximation when the
tree
tree edit distance
we also provide a novel static and dynamic decomposition achieving an o k log n -approximation when the tree edit distance is at most k
overall they are not yet reliable as standalone zero-shot reasoners but exhibit encouraging signs as complementary visual engines alongside dedicated
reasoning
multimodal reasoning
overall they are not yet reliable as standalone zero-shot reasoners but exhibit encouraging signs as complementary visual engines alongside dedicated reasoning models
the virial mass of clumps increases exponentially with this normalized
time
massive stars
the virial mass of clumps increases exponentially with this normalized time revealing an accelerating buildup of star-forming gas within protoclusters
we complement our theoretical results with experiments on various real-world
datasets
real-world datasets
we complement our theoretical results with experiments on various real-world datasets which show that the proposed sketches are lightweight and achieve consistently low error in practice
among them ones that minimize a regularized p th-order taylor expansion at each step have been shown to possess optimal global complexity which improves as
p
zeroth-order methods
among them ones that minimize a regularized p th-order taylor expansion at each step have been shown to possess optimal global complexity which improves as p increases
we find a total of 20 mechanisms of third-order
nonlinear
third-order nonlinear
we find a total of 20 mechanisms of third-order nonlinear transport by developing a comprehensive theory that treats the geometric effects and disorder scattering on an equal footing
weak almost sure convergence and linear convergence are also
established
linear convergence
weak almost sure convergence and linear convergence are also established under standard condition
images are high-dimensional and lossy or entangled latents make
dynamics
representation learning
images are high-dimensional and lossy or entangled latents make dynamics learning unnecessarily hard
measuring qubits currently takes milliseconds-much longer than the underlying quantum gate operations-making
readout
qubit readout
measuring qubits currently takes milliseconds-much longer than the underlying quantum gate operations-making readout the primary bottleneck in deploying quantum error correction
inspired by this principle we introduce a hierarchical multimodal recurrent neural network grounded in predictive
processing
predictive processing
inspired by this principle we introduce a hierarchical multimodal recurrent neural network grounded in predictive processing under the free-energy principle capable of directly integrating over 30 000-dimensional visuo-proprioceptive inputs without dimensionality reduction
we evaluate 15 foundation models across 79 problems spanning eight academic domains physics mathematics chemistry economics
biology
foundation models
we evaluate 15 foundation models across 79 problems spanning eight academic domains physics mathematics chemistry economics biology statistics calculus and optimization through three experimental phases 1 baseline establishment six models mixtral-8x7b phi-3 llama 3
this constraint naturally gives rise to spatial correlations between the states of neighboring nodes as the
infection
infectious individuals
this constraint naturally gives rise to spatial correlations between the states of neighboring nodes as the infection status of connected individuals becomes interdependent
the circumgalactic medium cgm is host to gas flows into and out of galaxies and regulates galaxy growth but the
multiphase
galaxy cgm
the circumgalactic medium cgm is host to gas flows into and out of galaxies and regulates galaxy growth but the multiphase diffuse gas in this region is challenging to observe
overall they are not yet reliable as standalone zero-shot reasoners but exhibit encouraging signs as complementary
visual
reasoning capabilities
overall they are not yet reliable as standalone zero-shot reasoners but exhibit encouraging signs as complementary visual engines alongside dedicated reasoning models
this paper develops a unified theoretical framework for detecting and estimating
boundaries
treatment assignment
this paper develops a unified theoretical framework for detecting and estimating boundaries in treatment effects across both spatial and temporal dimensions
in all the considered cases the resulting casimir force is attractive and the s-o
coupling
s-o coupling
in all the considered cases the resulting casimir force is attractive and the s-o coupling nu has impact on its magnitude
stakeholders across 21 european islands were consulted on climate and
land
land use
stakeholders across 21 european islands were consulted on climate and land use change issues affecting ecosystem services
a higher ionization component is needed for ne
x
ionized gas
a higher ionization component is needed for ne x absorption
we introduce a hybrid classical-quantum algorithm to compute dynamical correlation functions and excitation spectra in many-body quantum systems with a focus on
molecular
molecular dynamics
we introduce a hybrid classical-quantum algorithm to compute dynamical correlation functions and excitation spectra in many-body quantum systems with a focus on molecular systems
the code and synthetic dataset are available on
https
training data
the code and synthetic dataset are available on https github
posterior sampling by combining diffusion
models
diffusion models
posterior sampling by combining diffusion models with annealed langevin dynamics
while pruning and low-rank approximation have each demonstrated promising performance individually their synergy for llms
remains
llm raters
while pruning and low-rank approximation have each demonstrated promising performance individually their synergy for llms remains underexplored
these findings demonstrate the potential of ai
agents
ai systems
these findings demonstrate the potential of ai agents to move beyond process partners toward colleagues that share intent strengthen group dynamics and collaborate with humans to advance ideas
further enhancement of the breakdown voltage was achieved by tunneling leakage management using composite pt cap ptox
pt
ptox pt
further enhancement of the breakdown voltage was achieved by tunneling leakage management using composite pt cap ptox pt 1
while their behavior in equilibrium is well-understood theoretically the nonequilibrium regime at
high
molecular dynamics
while their behavior in equilibrium is well-understood theoretically the nonequilibrium regime at high excitation densities-where phenomena like electron-hole liquids emerge - is less explored
additionally our system enables object-level editing where physical items in the room can be transformed to their
virtual
virtual reality
additionally our system enables object-level editing where physical items in the room can be transformed to their virtual counterparts in a story
large cities lose their growth edge as urban
systems
large cities
large cities lose their growth edge as urban systems mature
our work not only clarifies the intimate connection between magnetism and cef in rare-earth compounds but more importantly it reveals a physical pathway to effectively tune
magnetic
magnetic properties
our work not only clarifies the intimate connection between magnetism and cef in rare-earth compounds but more importantly it reveals a physical pathway to effectively tune magnetic anisotropy via anisotropic lattice distortion induced by chemical pressure
the extent to which different neural or artificial neural networks models rely on equivalent representations to support similar tasks remains a central
question
neural representations
the extent to which different neural or artificial neural networks models rely on equivalent representations to support similar tasks remains a central question in neuroscience and machine learning
however brain signals infused with prior knowledge and associations exhibit a significant information asymmetry when compared to raw visual features still posing challenges for decoding
fmri
functional connectivity
however brain signals infused with prior knowledge and associations exhibit a significant information asymmetry when compared to raw visual features still posing challenges for decoding fmri representations under the supervision of images
to overcome this limitation we propose a data
fusion
data fusion
to overcome this limitation we propose a data fusion framework that leverages multiple data sources that are partially aligned with the target distribution
we highlight critical open questions and practical trade-offs that must be addressed offering multidisciplinary insights from engineering logic and law to guide future developments in legally compliant
autonomous
autonomous driving
we highlight critical open questions and practical trade-offs that must be addressed offering multidisciplinary insights from engineering logic and law to guide future developments in legally compliant autonomous driving systems
for a sample of masers the basic kinematic equations were solved by including the
galactic
galactic disk
for a sample of masers the basic kinematic equations were solved by including the galactic rotation parameters and the peculiar velocity of the sun as the unknown variables
by contrast in the unconditional setting diffusion models succeed with only an
l
diffusion models
by contrast in the unconditional setting diffusion models succeed with only an l 2 bound on the score error
we present glyph-sr a vision-language-guided
diffusion
language models
we present glyph-sr a vision-language-guided diffusion framework that aims to achieve both objectives jointly
we then propose novel estimators that are
asymptotically
efficiency bound
we then propose novel estimators that are asymptotically efficient achieving this theoretical bound
however its application is often hindered by low textbf
reward
reinforcement learning
however its application is often hindered by low textbf reward density in deep search scenarios where agents expend significant exploratory costs for infrequent and often null final rewards
theoretically we show that the generative models within the
bo
generative models
theoretically we show that the generative models within the bo process approximately follow a sequence of distributions which asymptotically concentrate at the global optima under certain conditions
large language models llms are catalyzing the development of autonomous
ai
artificial intelligence
large language models llms are catalyzing the development of autonomous ai research agents for scientific and engineering discovery
at the same time large language models llms are
increasingly
language models
at the same time large language models llms are increasingly used in health coaching yet cgm is rarely incorporated as a first-class signal
in this work we propose portool a reinforcement
learning
reinforcement learning rl
in this work we propose portool a reinforcement learning rl method that encourages a tool-use llm to explore various trajectories yielding the correct answer
we further analyze birefringent walk-off in
bulk
photonic crystal
we further analyze birefringent walk-off in bulk crystals and demonstrate that its apparent degradation of entanglement such as weakened transverse anti-correlations and inflated reid products can be corrected
experimental results show that lagmemo s memory module enables effective multi-modal open-vocabulary goal localization and that lagmemo outperforms state-of-the-art methods in multi-goal
visual
visual navigation
experimental results show that lagmemo s memory module enables effective multi-modal open-vocabulary goal localization and that lagmemo outperforms state-of-the-art methods in multi-goal visual navigation
we illustrate the framework in an empirical application estimating the
causal
causal effects
we illustrate the framework in an empirical application estimating the causal effect of private health insurance on health outcomes
specifically our dual-stage design includes both third-order nonlinear spectral broadening followed by a dedicated periodically poled
waveguide
waveguide modes
specifically our dual-stage design includes both third-order nonlinear spectral broadening followed by a dedicated periodically poled waveguide section performing efficient broadband intrapulse difference frequency generation
for ate estimation we estimate the propensity score through direct
bias-correction
bias-correction term
for ate estimation we estimate the propensity score through direct bias-correction term estimation
the probability of vacuum metastability and artificial
vacuum
vacuum metastable
the probability of vacuum metastability and artificial vacuum decay expert survey results
this is a concise pedagogical introduction to the dynamic field of
open
quantum networks
this is a concise pedagogical introduction to the dynamic field of open quantum systems governed by markovian master equations
ai-powered approaches specifically large language models llms natural
language
large language
ai-powered approaches specifically large language models llms natural language processing nlp and generative ai offer transformative solutions and reduce inefficiencies
distributed quantum computing dqc provides a promising route toward scalable quantum
computation
quantum advantage
distributed quantum computing dqc provides a promising route toward scalable quantum computation where entanglement-assisted locc and circuit knitting represent two complementary approaches
ai mathematician as a partner in advancing
mathematical
mathematical reasoning
ai mathematician as a partner in advancing mathematical discovery -- a case study in homogenization theory
including our target star-forming galaxies at z 6 detected by
alma
milky way
including our target star-forming galaxies at z 6 detected by alma are generally very young but more massive and brighter in uv than galaxies identified by only jwst
2024 develops riesz regression for automatic debiased machine learning which directly estimates the
riesz
riesz representer
2024 develops riesz regression for automatic debiased machine learning which directly estimates the riesz representer or equivalently the bias-correction term by minimizing the mean squared error
these findings suggest that geometry and tuning encode brain-region- or model-family-specific signatures while linearly decodable information tends to be more globally shared across
regions
brain regions
these findings suggest that geometry and tuning encode brain-region- or model-family-specific signatures while linearly decodable information tends to be more globally shared across regions or models
formulas that determine the least favourable spectral density matrices and the minimax robust spectral characteristics are proposed in the case where the spectral density matrices are not exactly known but a class of admissible
spectral
spectral density matrices
formulas that determine the least favourable spectral density matrices and the minimax robust spectral characteristics are proposed in the case where the spectral density matrices are not exactly known but a class of admissible spectral density matrices is given
more broadly they point to an intrinsic neural signature of adaptive brain function marked by efficient yet flexible network
organization
brain regions
more broadly they point to an intrinsic neural signature of adaptive brain function marked by efficient yet flexible network organization that may support creative and adaptive cognition
laplace noise user interference while retaining
competitive
signal-to-noise ratio
laplace noise user interference while retaining competitive accuracy under matched conditions
this work theoretically investigates possibilities of using the stimulated raman adiabatic passage stirap and its variants to control a coherent superposition of
quantum
quantum emitters
this work theoretically investigates possibilities of using the stimulated raman adiabatic passage stirap and its variants to control a coherent superposition of quantum states
training deep neural networks dnns with backpropagation bp achieves state-of-the-art accuracy but requires global error propagation and full parameterization leading to substantial
memory
deep network
training deep neural networks dnns with backpropagation bp achieves state-of-the-art accuracy but requires global error propagation and full parameterization leading to substantial memory and computational overhead
our results provide fundamental insights into light-matter
interactions
light-matter interactions
our results provide fundamental insights into light-matter interactions in solids at the nanoscale and are vital for optimally designing the new generation of absorption-based flexible optoelectronic devices
adaptive channel estimation and quantized feedback for ris assisted optical wireless
communication
communication systems
adaptive channel estimation and quantized feedback for ris assisted optical wireless communication systems
the p-stationary point enables the development of an efficient algorithm called appa which is guaranteed to converge to a p-stationary point within a finite number of iterations under a single mild assumption namely strong smoothness of the
objective
objective function
the p-stationary point enables the development of an efficient algorithm called appa which is guaranteed to converge to a p-stationary point within a finite number of iterations under a single mild assumption namely strong smoothness of the objective function over the unit box
this thesis presents a first-principles study of
excitons
electronic structure
this thesis presents a first-principles study of excitons in two-dimensional materials
these findings suggest that multimorbidity trajectories are shaped by robust shared biological and
epidemiological
comorbidity networks
these findings suggest that multimorbidity trajectories are shaped by robust shared biological and epidemiological mechanisms that transcend national healthcare contexts
the tri-infrastructure methodology and 79-problem benchmark enable longitudinal tracking of
reasoning
reasoning capabilities
the tri-infrastructure methodology and 79-problem benchmark enable longitudinal tracking of reasoning capabilities as foundation models evolve
additionally adaptation modulates the properties of the spatio-temporal activity patterns such as temporal and spatial frequencies and the speed of the
traveling
traveling waves
additionally adaptation modulates the properties of the spatio-temporal activity patterns such as temporal and spatial frequencies and the speed of the traveling waves all of which increase with increasing strength
kinodynamic constraints embedded in the tamp problem are verified by an off-the-shelf
motion
motion planning
kinodynamic constraints embedded in the tamp problem are verified by an off-the-shelf motion planner and physics simulator and a vlm guides exploring a tamp solution and backtracks the search based on visual rendering of the states
this chapter surveys mtl approaches based on
svm
support vector machines
this chapter surveys mtl approaches based on svm and twsvm highlighting shared representations task regularization and structural coupling strategies
order-unity star formation efficiencies sfe in early galaxies may explain the overabundance of bright galaxies observed by
jwst
quiescent galaxies
order-unity star formation efficiencies sfe in early galaxies may explain the overabundance of bright galaxies observed by jwst at high redshift
the edge detection task is essential in image processing aiming to
extract
feature extraction
the edge detection task is essential in image processing aiming to extract relevant information from an image
phase shifts switches and beam splits allow for the construction of arbitrary
quantum
photonic circuits
phase shifts switches and beam splits allow for the construction of arbitrary quantum gates
this work aims to reduce this gap by rigorously establishing the global convergence of the sequence generated by ripalm and proving its asymptotic super linear
convergence
superlinear convergence
this work aims to reduce this gap by rigorously establishing the global convergence of the sequence generated by ripalm and proving its asymptotic super linear convergence rate under standard assumptions
figuring out gas galaxies in enzo foggie xi circumgalactic
o
quiescent galaxies
figuring out gas galaxies in enzo foggie xi circumgalactic o vi emission traces clumpy inflowing recycled gas
this work establishes a clean dichotomy the optimal time complexity to support central string queries in
compressed
compressed indexing
this work establishes a clean dichotomy the optimal time complexity to support central string queries in compressed space is either theta log n log log n or theta log log n
our results demonstrate that rigorous boundary detection requires both
theoretical
effect boundaries
our results demonstrate that rigorous boundary detection requires both theoretical derivation from first principles and empirical validation of underlying physical assumptions
ai-powered approaches specifically large language models llms natural
language
artificial intelligence
ai-powered approaches specifically large language models llms natural language processing nlp and generative ai offer transformative solutions and reduce inefficiencies
to our knowledge this is the first algorithm to achieve an o log n
competitive
online algorithm
to our knowledge this is the first algorithm to achieve an o log n competitive ratio for non-trivial metrics beyond the i
our framework unifies riesz regression for automatic
debiased
debiased machine
our framework unifies riesz regression for automatic debiased machine learning covariate balancing targeted maximum likelihood estimation tmle and density-ratio estimation
the proposed motdiff consists of two key components 1 a new conditional diffusion framework that uses
multi-scale
image fusion
the proposed motdiff consists of two key components 1 a new conditional diffusion framework that uses multi-scale feature maps extracted from a single blurred image as a condition and 2 a new training method that can promote precise identification of a fine-grained motion trajectory consistent estimation of overall sha...
to systematically analyze these challenges we introduce a taxonomy categorizing existing
approaches
existing approaches
to systematically analyze these challenges we introduce a taxonomy categorizing existing approaches by their theoretical foundations architectural implementations and validation strategies
to illustrate this we construct a class of structured datasets where incremental adam
provably
sparse autoencoders
to illustrate this we construct a class of structured datasets where incremental adam provably converges to the ell_2 -max-margin classifier in contrast to the ell_ infty -max-margin bias of full-batch adam
in this paper we introduce a novel emph polybasic speculative
decoding
speculative decoding
in this paper we introduce a novel emph polybasic speculative decoding framework underpinned by a comprehensive theoretical analysis
in this work we study data-driven stabilization of linear time-invariant
systems
linear control
in this work we study data-driven stabilization of linear time-invariant systems using prior knowledge of system-theoretic properties specifically stabilizability and controllability
in recent years there has been growing interest in developing robots and
autonomous
autonomous driving
in recent years there has been growing interest in developing robots and autonomous systems that can interact with human in a more natural and intuitive way
existing automl solutions are unfortunately not directly applicable to time
series
time series classification
existing automl solutions are unfortunately not directly applicable to time series anomaly detection and no evaluation of time series-based approaches for model selection exists
in this work we present a clear and robust morphological analysis of a
sample
galaxy cgm
in this work we present a clear and robust morphological analysis of a sample of 190 galaxies at z 6 demonstrating that distinct bulge and disk components were already beginning to emerge during this early epoch
we evaluate our hierarchical reconstruction approach on three examples 1d translational motion 2d rotational motion and dynamic 3d scene deformation via
gaussian
gaussian splatting
we evaluate our hierarchical reconstruction approach on three examples 1d translational motion 2d rotational motion and dynamic 3d scene deformation via gaussian splatting